标题: | 代理人自我觉察能力对于个体积效与合作行为之研究 A Study on Agent Self-awareness for Individual Performance and Collaborative Behavior |
作者: | 陈敬华 Ching-Hua Chen 孙春在 Chuen-Tsai Sun 资讯科学与工程研究所 |
关键字: | 自我觉察;自我基模;学习型代理人;人工社会衡突;复杂行为浮现;Self-awareness;Self-Schema;Intelligent Agent;Artificial Society;Emergent Behavior;Social Network;Conflict |
公开日期: | 2004 |
摘要: | 本研究从智慧型代理人的角度出发,回应传统人工智慧领域中机器学习的核心问题:以世界模型为基础的学习型代理人的设计不足之处。为了使代理人具备自我学习的能力,换言之,类似人类的自我觉察能力,我们提出一套新颖的代理人认知学习架构,包含外在学习与内在认知双重概念,并相容于旧有的代理人架构。同时,为了有效验证此架构是强固的、可靠的,可广泛地应用在许多实际的状况,如电子商务环境、社会科学模拟系统,我们将代理人的目标与生存环境之间所造成的冲突,以反覆囚犯困局来模拟与实验,透过代理人的人格特质分析,我们提出一套以超我层次为自我觉察目标的代理人自觉模型,并以前述的反覆囚犯困局的实验结果,来分析自我觉察能力对于学习型代理人的个体绩效与合作行为的影响。 根据实验结果,本研究证明以超我层次为自我觉察目标的代理人自觉模型,可有效帮助学习型代理人提升表现成效,并使合作行为提前浮现。更进一步的模拟与分析,我们发现只需要少数的代理人具备自觉能力,即可提升整体代理人社会公益,这些实验结果也同时验证本研究提出的代理人认知学习架构。最后,我们期望本研究所探讨的方向与内容能让大家重新思考与重视自我觉察对学习型代理人设计的重要性。 The approach of this research, how intelligent agents learn, is to deal with a core problem of Machine Learning. The problem of traditional artificial intelligence lies in the flaw that learning agents are designed on the basis of World Model. To endue agents with Self-Learning ability, in other words, the ability similar to self-awareness of human beings, we proposed a new cognitive learning model, which includes both external learning and internal cognition compatible with the former structure, for agents, called Agent Cognition Learning Model (ACLM). In order to prove this model is robust, reliable, and extensively applicable for real situations such as E-commerce or social science simulation systems, we will simulate and experiment the conflict between the societal and self-interested goals of agents with Iterative Prisoner’s Dilemma on Social Networks. Through an analysis on personalities of agents, we proposed a Self-Awareness Model in Superego Level for agents. With the experimental results, we will analyze how individual performance and collaborative behavior of learning agents would be affected. The results of the experiments would demonstrate that the self-awareness model aim for superego level could certainly improve the performance of learning agents and expedite the emergence of collaborative behavior. Further simulation and analysis would show that as few of the agents are capable of self-awareness, the whole social benefits of agents would be enriched. These results also very strong the agent cognitive learning model proposed by our research. Finally, we hope this research could make people reconsider the importance of self-awareness in the design of self-learning agents. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT009223569 http://hdl.handle.net/11536/76619 |
显示于类别: | Thesis |
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